A General Framework for Assessing <i>In vitro/In vivo</i> Correlation as a Tool for Maximizing the Benefit‐Risk Ratio of a Treatment Using a Convolution‐Based Modeling Approach

Goméni, Roberto; Fang, Lanyan; Bressolle-Gomeni, Françoise; Spencer, Thomas; Faraone, Stephen V.; Babiskin, Andrew

doi:10.1002/psp4.12378

Cited by 13 publications

(12 citation statements)

References 18 publications

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“…Unfortunately, there is no single pharmacokinetic parameter that can describe this complex process. That said, recent pharmacokinetic-pharmacodynamic modeling using data for several ER MPH formulations has attempted to characterize the optimal drug release characteristics needed for optimal clinical benefit (discussed further in Section 7) [111,120].…”

Section: Pharmacokinetic Profile and The Resulting Pharmacokinetic-phmentioning

confidence: 99%

“…With OROS-MPH used as a reference drug, this modeling work by Gomeni and colleagues revealed that the optimal MPH release pattern for formulations exhibiting dual release characteristics is as follows: 1) approximately 20% of the dose released in the first process followed by the remainder of the dose in the second process; 2) a shorter time for delivering the initial fraction of the dose and a prolonged time for delivering the second fraction; and 3) a slower rate of release during both processes. Furthermore, an extension of this work proposed a convolution-based modeling approach to facilitate the development of drug formulations with optimal in vivo release properties by using in vivo-in vitro correlation (IVIVC) as a tool for maximizing the benefit-risk ratio of a treatment [120]. Specifically, a surface response analysis was used to identify the drug-related properties that could affect the clinical benefit of a treatment by connecting in vitro and in vivo drug release, in vivo drug release with pharmacokinetics, and pharmacokinetics with pharmacodynamics.…”

Section: Expert Opinionmentioning

confidence: 99%

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An update on the pharmacokinetic considerations in the treatment of ADHD with long-acting methylphenidate and amphetamine formulations

Childress

Komolova²,

Sallee³

2019

Expert Opinion on Drug Metabolism & Toxicology

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Introduction: Long-acting stimulant formulations are recommended as first-line pharmacotherapy for attention-deficit/hyperactivity disorder (ADHD). Over the past 20 years, extended-release (ER) methylphenidate (MPH) and amphetamine (AMP) formulations have evolved to include varying drug delivery technologies, enantiomers/salts, and dosage forms. All formulations are characterized by a unique pharmacokinetic profile that is closely mirrored by pharmacodynamic response allowing clinicians to individualize therapy based on their patient's clinical needs and dosing preferences. Areas covered: This review provides an update on the pharmacokinetic properties of approved and investigational ER MPH and AMP formulations and highlights pharmacokinetic features that clinicians should consider when selecting a long-acting stimulant. Expert opinion: Since there are no reliable biomarkers that can predict individualized response to longacting stimulants, clinicians need to consider their distinctive pharmacokinetic properties, including the pharmacokinetic profile, rate and extent of absorption, variability, dose proportionality, bioequivalence, and potential for accumulation. Clinicians also need to understand that certain factors can contribute to increased variability in pharmacokinetics and potentially affect outcomes. Less invasive, highthroughput techniques and novel time-based scales are being developed to advance research on the pharmacokinetic-pharmacodynamic relationships of stimulants. Model-based pharmacokineticpharmacodynamic approaches can be applied to aid the development of novel formulations and individualize therapy with existing drugs. ARTICLE HISTORYfor the treatment of ADHD. However, given their rapid absorption and metabolism, the therapeutic effects of IR stimulants typically wear off within a few hours, requiring twice-or thrice-daily dosing to achieve symptom control [19,20]. This presents a number of significant challenges for patients, including fluctuating peak and trough plasma concentrations that may increase the risk of adverse events or reduce efficacy; the inconvenience of multiple daily dosing, which may result in embarrassment, stigma, and lack of privacy, especially when administrating therapy during a school or work day; reduced treatment compliance; and the potential for diversion of these Schedule II drugs [17,[19][20][21][22][23][24]. Sustained-release (SR) formulations of MPH were initially developed to address these challenges. Unfortunately, they were not as effective as IR formulations and the reduced efficacy was attributed to acute tolerance due to a lack of a steep absorption phase and a flat (i.e. zero-order) drug delivery profile following peak levels [19,21,22]. Subsequently, an ascending (e.g. first-order) drug delivery profile was proposed to overcome or minimize this tachyphylaxis [21,22]. Based on this observation, several extended-release (ER) formulations of both MPH and AMP have since been developed with ascending plasma concentrations that mimic twice-or thrice-daily ad...

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Section: Pharmacokinetic Profile and The Resulting Pharmacokinetic-phmentioning

confidence: 99%

Section: Expert Opinionmentioning

confidence: 99%

An update on the pharmacokinetic considerations in the treatment of ADHD with long-acting methylphenidate and amphetamine formulations

Childress

Komolova²,

Sallee³

2019

Expert Opinion on Drug Metabolism & Toxicology

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“…20 Recently, a convolution-based modeling approach has been shown to represent a powerful and flexible tool for modeling complex pharmacokinetics of extended release (ER) and LAI products, and for maximizing the benefit-risk ratio of a treatment by optimizing the drug release properties using IVIVC and integrated PK/PD models. 21 Using this approach, the time course of the drug concentration can be described by convolving an input function with a disposition and elimination function when input and disposition functions are described by parametric models. A generalization of this method is now proposed for increasing the flexibility of the model and for providing an extended ability to characterize irregular drug release process.…”

Section: Introductionmentioning

confidence: 99%

“…Several pharmacokinetic strategies have been developed and applied to analyze such atypical absorption profiles, including the use of physiologically based pharmacokinetic approaches, 12 double or triple Weibull in vivo release models, 13,14 parallel zero‐order immediate release and, after a lag time, first‐order release, 15–17 transit compartments for delayed drug release, 18 combination of immediate first‐order release and transit compartments, 19 and inverse Gaussian density absorption 20 . Recently, a convolution‐based modeling approach was shown to represent a powerful and flexible tool for modeling complex pharmacokinetics of extended‐release and LAI products, and for maximizing the benefit‐risk ratio of a treatment by optimizing the drug release properties using IVIVC and integrated PK/pharmacodynamic models 21 …”

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confidence: 99%

Modeling Complex Pharmacokinetics of Long‐Acting Injectable Products Using Convolution‐Based Models With Nonparametric Input Functions

Goméni

Bressolle-Gomeni

2021

The Journal of Clinical Pharma

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The interest in the development and the therapeutic use of long-acting injectable (LAI) products for chronic or long-term treatments has grown exponentially. The complexity and the multi-phase drug release process represent serious issues for an effective modeling of the PK properties of LAI products. The objective of this paper was to show how convolutionbased models with piecewise-linear approximation of the nonlinear drug release function, can provide an enhanced modeling tool for: a) characterizing the complex PK profiles of LAI formulations with completely different drug release properties, and b) addressing key questions supporting the optimal development of LAI products by simulating the PK time course resulting from different dosing strategies. Convolution-based modeling and simulation were implemented in NONMEM and three case studies were presented to assess the performances of this new modeling approach using PK data of LAI products developed using different technologies and administered using different routes: microsphere technology and aqueous nanosuspension intramuscularly administered, and biodegradable polymer subcutaneously administered. The performance of the convolution-based modeling approach was compared to the performance of conventional parametric models using a reference dataset on theophylline. The results of the comparison indicated that the nonparametric input function provided a more accurate description of the data either in term of global measure of goodness of fit (i.e., AIC and BIC criteria) or in term of performance of the fitted model (i.e., the percent prediction error on Cmax and AUC 0-t).

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“…In extending the concept of modeling, Roberto Gomeni (Pharmacometrica, France) discussed general in silico frameworks for maximizing the benefit-risk ratio of a treatment. The net benefit of a treatment is usually defined by the relationship between potential clinical improvement and the risk of adverse events (Gomeni et al, 2019). He introduced the concept of convolution-based modeling as a means of optimizing the potential clinical benefit of new pharmacological treatments.…”

Section: Introductionmentioning

confidence: 99%

European Federation for Exploratory Medicines Development Lyon Conference 2019: The Changing Landscape of Early Medicines Development—Be Prepared

Hardman

Caplain²,

Rottey³

et al. 2019

Front. Pharmacol.

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The second biennial conference of the European Federation for Exploratory Medicines Development (EUFEMED) was the result of a continued effort of EUFEMED to gather all stakeholders of exploratory clinical drug development to evaluate and discuss recent developments in the field. The conference focused on how the landscape around early clinical development is changing and how clinical pharmacologists might prepare for these changes. A preconference workshop gave consideration to the impact that modeling and simulation, including physiology-based pharmacokinetic strategies, is having on the practice of clinical development. A second workshop looked at the challenges introduced by biological agents. The keynote address explored the potential role of virtual trials in early medicines development with emphasis on how models can help to understand and inform the drug development process. Presentations that followed covered a broad range of subjects including the potential impact of digital support on study performance in early phase development, extending from recruitment to remote data collection, lay person summaries, data transparency, and ethical considerations for trials in healthy subjects. The second day of the conference focused on future regulatory challenges in the field of early clinical development (including Brexit) and how to prepare for changes in the landscape. Subjects covered included new approaches and designs in oncology, the introduction of more complex study designs and digital biomarkers. Presentations given by invited speakers are published at .

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A General Framework for Assessing In vitro/In vivo Correlation as a Tool for Maximizing the Benefit‐Risk Ratio of a Treatment Using a Convolution‐Based Modeling Approach

Cited by 13 publications

References 18 publications

An update on the pharmacokinetic considerations in the treatment of ADHD with long-acting methylphenidate and amphetamine formulations

An update on the pharmacokinetic considerations in the treatment of ADHD with long-acting methylphenidate and amphetamine formulations

Modeling Complex Pharmacokinetics of Long‐Acting Injectable Products Using Convolution‐Based Models With Nonparametric Input Functions

European Federation for Exploratory Medicines Development Lyon Conference 2019: The Changing Landscape of Early Medicines Development—Be Prepared

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